Method and apparatus for monitoring of diastolic hemodynamics

- Cardiac Pacemakers, Inc.

A cardiac rhythm management system provides for ambulatory monitoring of hemodynamic performance based on quantitative measurements of heart sound related parameters for diagnostic and therapeutic purposes. Monitoring of such heart sound related parameters allows the cardiac rhythm management system to determine a need for delivering a therapy and/or therapy parameter adjustments based on conditions of a heart. This monitoring also allows a physician to observe or assess the hemodynamic performance for diagnosing and making therapeutic decisions. Because the conditions of the heart may fluctuate and may deteriorate significantly between physician visits, the ambulatory monitoring, performed on a continuous or periodic basis, ensures a prompt response by the cardiac rhythm management system that may save a life, prevent hospitalization, or prevent further deterioration of the heart.

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Description
CLAIM OF PRIORITY

This application is a continuation of and claims the benefit of priority under 35 U.S.C. § 120 to U.S. patent application Ser. No. 10/334,694, filed on Dec. 30, 2002, now issued as U.S. Pat. No. 7,972,275, which is hereby incorporated by reference herein in its entirety.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is related to co-pending, commonly assigned Siejko et al. U.S. patent application Ser. No. 10/307,896, entitled “PHONOCARDIOGRAPHIC IMAGE-BASED ATRIOVENTRICULAR DELAY OPTIMIZATION,” filed Dec. 2, 2002, now issued as U.S. Pat. No. 7,123,962, which is hereby incorporated by reference.

TECHNICAL FIELD

This document relates generally to cardiac rhythm management systems and particularly, but not by way of limitation, to such a system sensing heart sounds for monitoring, diagnosis, and therapy control.

BACKGROUND

A heart is the center of a person's circulatory system. It includes a complex electro-mechanical system performing two major pumping functions. The left portions of the heart, including the left atrium and the left ventricle, draw oxygenated blood from the lungs and pump it to the organs of the body to provide the organs with their metabolic needs for oxygen. The right portions of the heart, including the right atrium and the right ventricle, draw deoxygenated blood from the organs and pump it into the lungs where the blood gets oxygenated. These mechanical pumping functions are accomplished by contractions of the myocardium (heart muscles). In a normal heart, the sinus node, the heart's natural pacemaker, generates electrical signals, called action potentials, that propagate through an electrical conduction system to various regions of the heart to excite myocardial tissues in these regions. Coordinated delays in the propagations of the action potentials in a normal electrical conduction system cause the various regions of the heart to contract in synchrony such that the pumping functions are performed efficiently. Thus, the normal pumping functions of the heart, indicated by hemodynamic performance, require a normal electrical system to generate the action potentials and deliver them to designated portions of the myocardium with proper timing, a normal myocardium capable of contracting with sufficient strength, and a normal electro-mechanical association such that all regions of the heart are excitable by the action potentials.

The function of the electrical system is indicated by electrocardiography (ECG) with at least two electrodes placed in or about the heart to sense the action potentials. When the heart beats irregularly or otherwise abnormally, one or more ECG signals indicate that contractions at various cardiac regions are chaotic and unsynchronized. Such conditions are known as cardiac arrhythmias. Cardiac arrhythmias result in a reduced pumping efficiency of the heart, and hence, diminished blood circulation. Examples of such arrhythmias include bradyarrhythmias, that is, hearts that beat too slowly or irregularly, and tachyarrhythmias, that is, hearts that beat too quickly. A patient may also suffer from weakened contraction strength related to deterioration of the myocardium. This further reduces the pumping efficiency. For example, a heart failure patient suffers from an abnormal electrical conduction system with excessive conduction delays and deteriorated heart muscles that result in asynchronous and weak heart contractions, and hence, reduced pumping efficiency, or poor hemodynamic performance. Thus, in addition to ECG, the function of the mechanical system and the electro-mechanical association need to be measured to assess the overall pumping performance of the heart.

Characteristics of heart sounds are known to be indicative of various mechanical properties and activities of the heart. Measurements performed with synchronously recorded ECG and heart sounds provide for quantitative indications of the electro-mechanical association. For example, amplitudes of the third heart sound (S3) and fourth heart sound (S4) are related to filling pressures of the left ventricle during diastole. Fundamental frequencies of S3 and S4 are related to ventricular stiffness and dimension. Chronic changes in S3 amplitude is correlated to left ventricular chamber stiffness and degree of restrictive filling. Change in the interval between atrial contraction and S4 is correlated to the changes in left ventricular end of diastolic pressure. Such parameters, being correlated to the heart's mechanical properties and electromechanical association, quantitatively indicate abnormal cardiac conditions, including degrees of severity, and need of appropriate therapies.

For these and other reasons, there is a need for a system providing for cardiac therapy based on parameters related to heart sounds.

SUMMARY

A cardiac rhythm management system provides for ambulatory monitoring of hemodynamic performance based on quantitative measurements of heart sound related parameters for diagnostic and therapeutic purposes. Monitoring of such heart sound related parameters allows the cardiac rhythm management system to determine a need for delivering a therapy and/or therapy parameter adjustments based on conditions of a heart. This monitoring also allows a physician to observe or assess the hemodynamic performance for diagnosing and making therapeutic decisions. Because the conditions of the heart may fluctuate and may deteriorate significantly between physician visits, the ambulatory monitoring, performed on a continuous or periodic basis, ensures a prompt response by the cardiac rhythm management system that may save a life, prevent hospitalization, or prevent further deterioration of the heart.

In one embodiment, a system includes an acoustic sensor, a cardiac sensing circuit, a heart sound detector, a parameter generator, a processor, and a therapy circuit. The acoustic sensor senses an acoustic energy and produces an acoustic sensor signal indicative heart sounds. The cardiac sensing circuit senses a cardiac signal indicative of cardiac electrical events. The heart sound detector detects selected heart sounds based on the acoustic sensor signal and the cardiac signal. The parameter generator generates values of at least one predetermined parameter related to the selected heart sounds. The processor includes a trending analyzer that produces and analyzes at least one trend related to the selected heart sounds based on the values of the predetermined parameter. The therapy circuit delivers cardiac therapy with at least one therapy parameter determined based on the trend.

In another embodiment, an acoustic energy is sensed to produce an acoustic sensor signal indicative heart sounds. One or more cardiac signals indicative of cardiac electrical events are also sensed. Selected heart sounds are detected. Parameter values related to the selected heart sounds and selected cardiac electrical events are generated. Selected parameter values, which are associated with one or more types of the selected heart sounds, are analyzed to produce at least one trend. A therapy, with at least one parameter determined based on the trend, is delivered.

In yet another embodiment, a cardiac rhythm management system includes an implantable device. The implantable device includes an acoustic sensor, a cardiac sensing circuit, a gating module, a heart sound detector, a measurement module, and a therapy circuit. The acoustic sensor senses an acoustic energy to produce an acoustic sensor signal indicative heart sounds. The cardiac sensing circuit senses at least one cardiac signal indicative of cardiac electrical events. The gating module generates heart sound detection windows each timed for detection of one of selected heart sounds based on a time of occurrence of one of selected cardiac electrical events. The heart sound detector detects the selected heart sounds. The measurement module generates parameter values related to the selected heart sounds. The therapy circuit delivers a therapy based on the parameter values.

This summary is intended not to limit the claimed subject matter, and the scope of the invention is defined by attached claims and their equivalents.

BRIEF DESCRIPTION OF THE DRAWINGS

In the drawings, which are not necessarily drawn to scale, like numerals describe similar components throughout the several views. The drawings illustrate generally, by way of example, but not by way of limitation, various embodiments discussed in the present document.

FIG. 1 is a block diagram illustrating an embodiment of a heart-sound based hemodynamics monitoring and therapy control system.

FIG. 2 is an illustration of an embodiment of a method for detecting selected heart sounds.

FIG. 3 is a block diagram illustrating an embodiment of a measurement module of the system of FIG. 1.

FIG. 4 is a flow chart illustrating an embodiment of a method for hemodynamics monitoring and therapy control using the system of FIG. 1.

FIG. 5 is an illustration of an embodiment of portions of a cardiac rhythm management system incorporating heart-sound based hemodynamics monitoring and therapy control and portions of an environment in which it is used.

FIG. 6 is a block diagram illustrating a specific embodiment of portions of the cardiac rhythm management system of FIG. 5.

FIG. 7 is a block diagram illustrating another specific embodiment of portions of the cardiac rhythm management system of FIG. 5.

 DETAILED DESCRIPTION

In the following detailed description, reference is made to the accompanying drawings that form a part hereof, and in which is shown, by way of illustration, specific embodiments in which the invention may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the invention, and it is to be understood that the embodiments may be combined, or that other embodiments may be utilized and that structural, logical and electrical changes may be made without departing from the scope of the present invention. The following detailed description is, therefore, not to be taken in a limiting sense, and the scope of the present invention is defined by the appended claims and their equivalents.

This document discusses, among other things, a cardiac rhythm management system monitoring heart sounds indicative of a heart's mechanical events related to the heart's pumping functions and hemodynamic performance to allow, among other things, diagnosis of cardiac conditions and selection of therapies treating the cardiac conditions. The cardiac rhythm management systems include systems having, for example, pacemakers, cardioverter/defibrillators, pacemaker/defibrillators, and cardiac resynchronization therapy (CRT) devices. One specific example of a cardiac rhythm management system that monitors and analyses heart sounds is described in co-pending, commonly assigned Siejko et al. U.S. patent application Ser. No. 10/307,896, entitled “PHONOCARDIOGRAPHIC IMAGE-BASED ATRIOVENTRICULAR DELAY OPTIMIZATION,” filed Dec. 2, 2002, now issued as U.S. Pat. No. 7,123,962, which is hereby incorporated by reference in its entirety. However, it is to be understood that the present methods and apparatuses may be employed in other types of medical devices, including, but not being limited to, drug delivery systems and various types of cardiac monitoring devices.

Known and studied heart sounds include the “first heart sound” or S1, the “second heart sound” or S2, the “third heart sound” or S3, the “fourth heart sound” or S4, and their various sub-components. S1 is known to be indicative of, among other things, mitral valve closure, tricuspid valve closure, and aortic valve opening. S2 is known to be indicative of, among other things, aortic valve closure and pulmonary valve closure. S3 is known to be a ventricular diastolic filling sound often indicative of certain pathological conditions including heart failure. S4 is known to be a ventricular diastolic filling sound resulted from atrial contraction and is usually indicative of pathological conditions. The term “heart sound” hereinafter refers to any heart sound (e.g., S1) and any components thereof (e.g., M1 component of S1, indicative of Mitral valve closure).

Throughout this document, “heart sound” includes audible and inaudible mechanical vibrations caused by cardiac activity that can be sensed with an accelerometer. Accordingly, the scope of “acoustic energy” in this document extends to energies associated with such mechanical vibrations.

Throughout this document, “user” refers to a physician or other caregiver who examines and/or treats a patient using one or more of the methods and apparatuses reported in the present document. Unless noted otherwise, S1, S2, S3, and S4 refer to the first, second, third, and fourth heart sounds, respectively, as a heart sound type, or as one or more occurrences of the corresponding type heart sounds, depending on the context.

FIG. 1 is a block diagram illustrating an embodiment of a heart-sound based hemodynamics monitoring and therapy control system 100. System 100 includes, among other things, an acoustic sensor 110, a sensor interface module 120, a cardiac sensing circuit 112, a heart sound detector 130, a parameter generator 140, a data acquisition timer 118, a parameter processor 160, and a therapy circuit 170. In one embodiment, system 100 is a totally implantable system adapted to be implanted into a patient. In an alternative embodiment, system 100 is an external system that does not include any implantable component. In another alternative embodiment, system 100 includes both implantable and external components.

Acoustic sensor 110 senses an acoustic energy or mechanical vibration energy related to cardiac mechanical activities and converts the acoustic energy to an acoustic sensor signal indicative of heart sounds. The acoustic sensor signal is an electrical signal indicative of timing, strength, and frequency characteristics related to the heart sounds. Acoustic sensor 110 is disposed in a heart, or near the heart in a location where the acoustic energy related to the cardiac mechanical activities can be sensed. In one embodiment, acoustic sensor 110 includes an accelerometer disposed in or near a heart. In another embodiment, acoustic sensor 110 includes a microphone disposed in or near a heart.

Sensor interface module 120 has a signal input connected to the output of acoustic sensor 110 to receive the acoustic sensor signal. It processes the acoustic sensor signal to prepare for detection of selected type heart sounds. The selected type heart sounds are heart sounds selected for a purpose of monitoring a patient's hemodynamic performance indicated by the measurable characteristics of these heart sounds. In one specific embodiment, the selected type heart sounds includes S3 and S4, which are indicative of ventricular diastolic hemodynamic performance. Sensor interface module includes a signal conditioning circuit 122, a digitizer 124, and a digital filter 126. Signal conditioning circuit 122 receives the acoustic sensor signal as an analog signal from acoustic sensor 110, and performs initial conditioning of the acoustic sensor signal. In one embodiment, signal conditioning circuit 122 improves the signal-to-noise ratio of the acoustic sensor signal. It includes an amplifier and a filter to amplify the acoustic sensor signal while reducing the noise therein. In one embodiment, the filter is an analog filter that substantially reduces amplitudes of noises that are not within the frequency spectrum of the selected type heart sounds. In another embodiment, the filter substantially reduces amplitudes of noises as well as components of the acoustic sensor signal that are outside of the frequency range of the selected type heart sounds. Digitizer 124 digitizes the filtered acoustic sensor signal by sampling it at a predetermined rate. In one embodiment, the sampling rate is programmable and determined based on known frequency characteristics of the heart sounds to be detected. In one embodiment, digitizer 124 samples the acoustic sensor signal only during predetermined periods of time where the selected type heart sounds are most likely to be present. This saves electrical energy required for processing the acoustic sensor signal and/or allows a higher resolution of the digitized acoustic sensor signal without substantially increasing the electrical energy required for processing. Energy conservation is of particular importance when system 100 is a totally implantable system or includes implantable components. Digital filter 126 substantially reduces amplitudes for all components of the acoustic sensor signal except the selected type heart sounds, which are to be detected by heart sound detector 130, thereby enhancing the indications of the selected type heart sounds. In one embodiment, digital filter 126 includes a band-pass filter having cutoff frequencies determined based on the frequency spectrum of the selected type heart sounds. It is to be understood, however, that the cutoff frequencies are dependent on the purpose of detection and need not cover exactly the known spectrum of particular heart sounds. In one specific embodiment, digital filter 126 is band-pass filter having a low cutoff frequency in the range of 5 to 20 Hz and a high cutoff frequency in the range of 30 to 120 Hz selected for the purpose of detecting S3 and S4. One example of a suitable pass band for digital filter 126 for detection of S3 and S4 for monitoring ventricular diastolic hemodynamics includes a low cutoff frequency of 10 Hz and a high cutoff frequency of 60 Hz. In one specific embodiment, digital filter 126 is an envelope detector type filter. In one embodiment, digital filter 126 is a programmable digital filter in which at least one of the cutoff frequencies is programmable. This allows a dynamic selection of heart sounds for detection without a need for additional circuitry.

Cardiac sensing circuit 112 senses at least one cardiac signal indicative of cardiac electrical events that are needed for detection and measurements related to the heart sounds and/or their components. In one embodiment, the cardiac signal includes a surface ECG signal. In another embodiment, the cardiac signal includes an intracardiac ECG signal that is also referred to as an electrogram. Cardiac sensing circuit 112 includes a sensing amplifier to sense the cardiac signal, a cardiac events detector to detect the cardiac electrical events, and an event marker generator to label each detected cardiac electrical event with an event marker indicative of the timing and type of the detected cardiac electrical event. The detected electrical events include, by not limited to, selected atrial and ventricular contractions. The atrial and ventricular contractions include spontaneous contractions and artificially stimulated contractions.

Heart sound detector 130 detects the selected type heart sounds. In one embodiment, heart sound detector 130 detects the selected type heart sounds based on the acoustic sensor signal. In another embodiment, heart sound detector 130 detects the selected type heart sounds based on the acoustic sensor signal and the cardiac signal sensed by cardiac sensing circuit 112. In one embodiment, heart sound detector includes a gating module 132 and a detection module 134. Gating module 132 receives the acoustic sensor signal from sensor interface module 120 and the cardiac signal from cardiac sensing circuit 112. In one embodiment, the cardiac signal received by gating module 132 includes event makers representing the detected cardiac electrical events that allow or facilitate detection of the selected type heart sounds. Gating module 132 generates heart sound detection windows each timed for detection of one of the selected type heart sounds based on a time of occurrence of one of cardiac electrical events. FIG. 2 illustrates, by way of example, but not by way of limitation, a heart sound detection window. As illustrated in FIG. 2, a cardiac signal 200 indicates a heart contraction 202. An event marker signal 210, which is a representation of cardiac signal 200, includes an event marker 212 representing heart contraction 202. An acoustic sensor signal 230, simultaneously recorded with cardiac signal 200, includes an indication of a heart sound 235. Based on available medical knowledge including statistical information available for an individual patient, heart sound 235 is substantially probable to occur within a time period T2 which starts after a time period T1 triggered by event marker 212 representing heart contraction 202. Thus, gating module 132 generates a heart sound detection window having a duration of T2 at the end of T1 following each heart contraction used for detection of the selected type heart sounds. In another embodiment, another heart sound (of a different type than the selected type) substitutes heart contraction 202 to trigger T1, and gating module 132 generates the heart sound detection window T2 at the end of T1 following each heart sound used for detection of the selected type heart sounds. In one embodiment, the heart sound detection windows are used to conserve energy and/or computational resources of system 100 by limiting the need for detection and subsequent computations to periods within the heart sound detection windows. In another embodiment, it is difficult or practically impossible to differentiate one type of the heart sounds from another by amplitude or frequency spectrum. This necessitates a method of detection that is not based on the amplitude or frequency spectrum of the selected type heart sounds. One feasible method includes the use one or more heart sound detection windows each corresponding to one or more types of heart sounds, thus allowing detections of heart sounds based on their predicted ranges of time of occurrence. Durations of the windows are determined based on an empirical study on the timing of each type of heart sounds relative to a type of cardiac. Heart sound detector 134 detects the selected type heart sounds. In one embodiment, heart sound detector 134 detects the selected type heart sounds within the one or more heart sound detection windows. In one embodiment, heart sound detector 134 includes one or more comparators to detect the selected type heart sounds by comparing the amplitude of the acoustic sensor signal during the one or more heart sound detection windows with one or more predetermined detection thresholds.

Following the detections of the selected type heart sounds by heart sound detector 130, parameter generator 140 makes measurements to generate parameter values of at least one predetermined parameter related to the detected heart sounds. In one embodiment, such a parameter value is measured from one detected heart sound. In another embodiment, the parameter value is calculated based on measurement of several detected heart sounds of the same type. The parameter values indicate the patient's hemodynamic performance, either directly or after further processing as discussed below. Parameter generator 140 includes a measurement module 150 to make measurements on the acoustic sensor signal. The measurements are timed with the detections of the selected type heart sounds. In one embodiment, measurement module 150 receives the acoustic sensor signal from heart sound detector 130 and the cardiac signal from cardiac sensing circuit 112. FIG. 3 is a block diagram that illustrates, by way of example, but not by way of limitation, components of measurement module 150. As illustrated in FIG. 3, measurement module 150 includes a strength detector 351, a relative strength detector 352, a duration timer 353, an electromechanical interval timer 354, a mechanical interval timer 355, and a frequency analyzer 356. Strength detector 351 measures amplitudes each associated with a detected heart sound. Relative strength detector 352 determines differences each between amplitudes associated with two detected heart sounds. Duration timer 353 measures durations each associated with a detected heart sound. Electromechanical interval timer 354 measures electromechanical time intervals each between a detected heart sound and a cardiac electrical event detected from the cardiac signal. Mechanical interval time 355 measures mechanical time intervals each between two detected heart sounds. Frequency analyzer 356 computes fundamental and/or harmonic frequencies each associated with a detected heart sound. In one embodiment, measurement module 150 calculate one or more parameter values each based on several values of a predetermined parameter measured by one of the components of measurement module 150. In one specific embodiment, measurement module 150 calculates the one or more parameter values each being an average of the several values of the predetermined parameter. Because of the nature and property of the acoustic sensor, the parameter values output from measurement module 150 may includes those affected by background interference. For example, when the acoustic sensor is an accelerometer, the acoustic sensor signal may indicate a patient's physical activities in addition to the heart sounds. When the acoustic sensor is a microphone, the acoustic sensor signal may indicate talking and other environment sounds in addition to the heart sounds. Thus, in one embodiment, parameter generator 140 includes a screening module 144 to exclude parameter values resulted from measurements performed when a background noise level exceeds a predetermined threshold. In one embodiment, a noise monitoring module 142 measures the background noise level. In one specific embodiment, noise monitoring module 142 includes an activity sensor that senses a patient's physical activities and an activity sensor interface module to convert the physical activities to the background noise level. In another specific embodiment, noise monitoring module includes a further sensor interface module coupled to acoustic sensor 110, which senses the patient's physical activities in addition to the acoustic energy related to the patient's cardiac mechanical activities. When acoustic sensor 110 includes an accelerometer, the further sensor interface module includes an activity level detector to produce the background noise level signal indicative of the patient's physical activities. The activity level as indicated by the acoustic sensor signal has a distinctively higher amplitude than the heart sounds. Thus, the activity level detector distinguishes the patient's physical activities from the heart sounds by using a predetermined activity level threshold. In one embodiment, parameter generator 140 includes a memory circuit 146 to store the parameter values generated by measurement module 150. In another embodiment, memory 146 stores only parameters screened by screening module 144.

Data acquisition enabler 118 controls the timing of overall data acquisition by timing the enablement of selected system components including at least one or more of acoustic sensor 110, sensor interface module 120, cardiac sensing circuit 112, heart sound detector 130, and parameter generator 140. In one embodiment, data acquisition enabler 118 enables the selected system components in response to an external command, such as given by the user. In another embodiment, data acquisition enabler 118 includes a data acquisition timer to enable the selected system components on a predetermined schedule. In one specific embodiment, the data acquisition timer enables the selected system components on a predetermined periodic basis. In another specific embodiment, if parameter generator 140 is unable to generate required parameter values on the predetermined schedule, for example, because the background noises exceeds the predetermined level when the selected system components are enabled, data acquisition enabler 118 modifies the predetermined schedule by introducing at least one delay to ensure that all the desired parameter values are obtained.

Parameter processor 160 processes the parameter values received from parameter generator 140. In one embodiment, parameter processor 160 includes a statistical processor 162, a trending analyzer 164, and an alert signal generator 166. Statistical processor 162 analyzes the parameter values generated by parameter generator 140 for a predetermined period of time. Trending analyzer 164 produces at least one trend related to the selected type heart sounds. The trend is a hemodynamic performance trend indicative of one or more cardiac conditions. In one embodiment, the trend is a plot of parameter values of one selected parameter related to the detected heart sounds over a predetermined period of time. In another embodiment, the trend is a plot of values derived for the parameter values as a result of the statistical process over the predetermined period of time. Alert signal generator 166 generates an alert signal indicative of a presence of the one or more cardiac conditions indicated by the at least one trend. In one embodiment, alert signal generator 166 includes a comparator. The comparator has a first input to receive the at least one trend, a second input representative of a predetermined threshold level, and an output indicative of the presence of the one or more clinical conditions when the at least one trend exceeds the predetermined threshold level. In one further embodiment, alert signal generator 166 includes a threshold generator that generates an adaptive threshold level based on at least one previously produced trend, such that the predetermined threshold is dynamically adjustable based on the patient's changing cardiac conditions.

Therapy circuit 170 includes, by way of example, but not by way of limitation, one or more of a pacing circuit, a defibrillation circuit, a cardiac resynchronization circuit, and a drug delivery circuit. It includes a therapy controller to execute a predetermined therapy algorithm that times therapy deliveries based on the processed cardiac signal and acoustic sensor signal. In one embodiment, the therapy controller receives at least one of selected parameter values generated by parameter generator 140, the at least one trend generated by trending analyzer 164, and the alert signal generated by alert signal generator 166, based on which it produces or adjusts one or more therapy parameters.

FIG. 4 is a flow chart illustrating an embodiment of a method for hemodynamics monitoring and therapy control using system 100. At 400, data acquisition for the hemodynamics monitoring and therapy control begins. In one embodiment, the data acquisition begins as system 100 is activated. In one embodiment, the data acquisition begins in response to a user command. In another embodiment, the data acquisition begins at a predetermined time or upon a predetermined triggering event. In one embodiment, the date acquisition lasts for a predetermined duration after it begins. In one specific embodiment, the data acquisition begins on a predetermined periodic basis and lasts for a predetermined duration.

At 402, acoustic sensor 110 senses the acoustic energy related to cardiac mechanical activities and converts the acoustic energy to an acoustic sensor signal indicative heart sounds. In one embodiment, acoustic sensor 110 senses an acceleration indicative of the acoustic energy.

At 410, sensor interface module 410 processes the acoustic sensor signal to prepare for heart sound detection. In one embodiment, the acoustic sensor signal is amplified and filtered to increase its signal-to-noise ratio. Then, the acoustic sensor signal is digitized to the form of binary data. The digitized acoustic sensor signal is filtered to enhance indications of the selected type heart sounds. In one embodiment, the digitized acoustic sensor signal is filtered with at least one cutoff frequency determined based on the frequency spectrum of the selected type heart sounds.

At 420, heart sound detector 130 generates heart sound detection windows each timed for detecting one of the selected type heart sounds. The heart sound detection windows are each triggered by one of selected cardiac electrical events detected from the cardiac signal sensed at 404. In one embodiment, the selected cardiac electrical events include at least one of spontaneous or artificially stimulated atrial and ventricular contractions. In one embodiment, the selected cardiac electrical events are each represented by a predetermined event marker. In one specific embodiment, At 425, the selected type heart sounds are detected. In one embodiment, each of the selected type heart sounds is detected when the amplitude of the acoustic sensor signal exceeds a predetermined threshold level.

At 430, parameter generator 140 generates the parameter values of at least one parameter related to the detected heart sounds based on the acoustic sensor signal produced at 400 and/or the cardiac signal sensed at 404. Such parameter values include, by way of example, but not by way of limitation, one or more of (i) an amplitude associated with one or one selected type of the selected type heart sounds; (ii) a relative strength being differences between amplitudes associated with two or two selected types of the selected type heart sounds; (iii) a duration associated with one or one selected type of the selected type heart sounds; (iv) an electromechanical time intervals between one or one selected type of the selected type heart sounds and one or one type of selected type cardiac electrical events; (v) a mechanical time interval between two or two selected types of the selected type heart sounds; and (vi) a fundamental or harmonic frequency associated with one or one selected type of the selected type heart sounds. In one embodiment, parameter values related to S3 and/or S4 are measured and/or calculated for the purpose of monitoring ventricular diastolic hemodynamic performance. The parameter values of one or more of the following parameters are generated: (i) peak amplitude of S3; (ii) time of onset of S3 relative to onset of S2; (iii) duration of S3; (iv) fundamental frequency if S3; (v) time of occurrence of S3 relative to the subsequently adjacent atrial contraction; (vi) peak amplitude of S4; (vii) time interval between atrial contraction and the subsequently adjacent S4; (viii) fundamental frequency of S4; (ix) duration of S4; (x) time of occurrence of S4 relative to the subsequently adjacent ventricular contraction; and (xi) amplitude of S4 relative to amplitude of S3. In one embodiment, parameter generator 140 screens out noisy values of the parameter values measured at 435. Such noisy values include parameter values measured when the background noise level exceeds a predetermined threshold. In one embodiment, the patient's physical activities are sensed at 406 to produce an activity level signal indicative of the background noise level. In one specific embodiment, the activity level signal is derived from the same acoustic sensor signal from which the selected type heart sounds are detected. This is possible because the patient's physical activities are typically indicated with amplitudes that are distinctively higher than the amplitudes of the selected type heart sounds.

At 440, the parameter values are stored in memory circuit 146 or other storage medium. In one embodiment, system 100 uses the parameter values directly to control delivery of at least one therapy with at least one therapy parameter being a function of the parameter values. In another embodiment, the parameter values are further processed and analyzed by system 100 for monitoring, diagnosis, and/or therapy control purposes. In yet another embodiment, the stored parameter values are transferred to another system, such as a computer separated from system 100, for further processing and/or analysis.

At 450, parameter processor 160 statistically processes the parameter values. The statistical process includes analyzing the parameter values of the at least one parameter related to the detected heart sounds in relation to historical values of that parameter measured during a predetermined period of time. The outcome of the statistical process reveals changes in cardiac conditions reflected in the characteristics of the selected type heart sounds. In one embodiment, the outcome of the statistical process reveals changes in ventricular diastolic filling patterns during the predetermined period of time. In one specific embodiment, the predetermined period of time ranges from 1 day to 3 months.

At 460, parameter processor 160 produces at least one hemodynamic performance trend related to the selected type heart sounds. In one embodiment, parameter processor 160 produces the at least one trend based on the outcome of the statistical analysis. In one embodiment, one or more trends quantitatively present one or more ventricular diastolic filling pattern changes during a predetermined duration. In one embodiment, parameter processor 160 plots the parameter values of the at least one parameter related to the detected heart sounds versus time. In another embodiment, parameter processor 160 statistically processes the parameter values of the at least one parameter related to the detected heart sounds and plots the result. At 465, the one or more trends are analyzed for indication of cardiac conditions. In one embodiment, the values of each trend are compared to a predetermined threshold level, and a predefined cardiac condition is indicated when any value exceeds the predetermined threshold level. In one embodiment, the predetermined threshold level is determined based on at least one previously produced trend.

At 475, an alert signal is generated when a cardiac condition is indicated by the at least one hemodynamic performance trend at 470. The alert signal notifies the user of the cardiac condition that may need medical attention. In one embodiment, the cardiac condition requires delivery of a therapy. In another embodiment, the alert signal indicates a need for changing one or more therapy parameters.

In one embodiment, a therapy is delivered in response to the alert signal at 480. The therapy includes one or more of, for example, a pacing therapy, a defibrillation therapy, a cardiac resynchronization therapy, any other electrical stimulation therapy, and a drug therapy. The type of the therapy as therapy parameters are determined based on the at least one trend and/or selected values of the at least one parameter related to the detected heart sounds. In one specific embodiment, therapy circuit 170 delivers the therapy. In another embodiment, one or more therapy parameters are adjusted in response to the alert signal, and the new therapy parameters are determined based on the at least one trend and/or the selected values of the at least one parameter related to the detected heart sounds. In an alternative embodiment, the therapy delivery or the therapy parameter adjustments are not dependent on the alert signal. The at least one trend and/or the selected values of the at least one parameter related to the detected heart sounds directly determine the need for the therapy delivery or the therapy parameter adjustments.

Many embodiments combining the present method with available medical knowledge will be apparent to those of skill in the art. In one example, the fundamental frequency (also referred to as the pitch) of S3 is correlated to the stiffness of the left ventricular wall during the rapid filling phase of diastole. The wall stiffness is proportional to diastolic pressure in the left ventricle and to the thickness of the left ventricular wall. Therefore, an increase in the pitch of S3 is used to indicate one or more of an elevated left ventricular filling pressure and a thickened left ventricular wall. The elevation of the left ventricular filling pressure and/or the increase of the left ventricular wall thickness may reach a degree, represented by predetermined thresholds of S3 fundamental frequency, that requires an application of adjustment of a therapy. In another example, the amplitude of S3 is directly related to the rate of deceleration of blood flow into the left ventricle during the rapid filling phase of diastole. An increase in amplitude of S3 can be used to indicate an elevation of left atrial filling pressure, an increase in stiffness of the left ventricle, or both, which represent a restrictive filling pattern associated with heart failure. Therefore, the trend of S3 amplitude is useful in monitoring cardiac mechanical properties related to heart failure. In yet another example, the elevated filling pressures cause pulmonary edema. Thus, a physician determines the need of a drug therapy to relieve the elevated pressures based on one or more trends of parameters related to S3. These are a few examples, among many possible embodiments, illustrating how system 100 is used. In general, trends of any of the measured parameter values can be used individually, jointly, and/or in combination with other trends related to cardiac functions.

FIG. 5 is an illustration of an embodiment of portions of a cardiac rhythm management system 599 and portions of an environment in which it is used. System 599 incorporates a heart-sound based hemodynamics monitoring and therapy control system such as system 100. In one embodiment, cardiac rhythm management system 599 includes an implanted system 505, an external system 580, and a telemetry link 570 providing for communication between implanted system 505 and external system 580. Implanted system 505 includes an implanted device 506 and a lead system 508. Implanted device 506 is implanted within a patient's body 502 and coupled to the patient's heart 501 via lead system 508. Examples of implanted device 506 include pacemakers, cardioverter/defibrillators, pacemaker/defibrillators, cardiac resynchronization devices, and drug delivery devices. External system 580 is a patient management system including an external device 585 in proximity of implanted device 502, a remote device 595 in a relatively distant location, and a telecommunication system 590 linking external device 585 and remote device 595. An example of such a patient management system is discussed in Hatlestad et al., “ADVANCED PATIENT MANAGEMENT FOR DEFINING, IDENTIFYING AND USING PREDETERMINED HEALTH-RELATED EVENTS,” application Ser. No. 10/323,604, filed on Dec. 18, 2002, assigned to Cardiac Pacemakers, Inc., the specification of which is incorporated herein by reference in its entirety. In one embodiment, telemetry link 570 is an inductive telemetry link. In an alternative embodiment, telemetry link 570 is a far-field radio-frequency telemetry link. In one embodiment, telemetry link 570 provides for data transmission from implanted device 506 to external device 585. This may include, for example, transmitting real-time physiological data acquired by implanted device 506, extracting physiological data acquired by and stored in implanted device 506, extracting therapy history data stored in implanted device 506, and extracting data indicating an operational status of implanted device 506 (e.g., battery status and lead impedance). In a further embodiment, telemetry link 570 provides for data transmission from external device 585 to implanted device 506. This may include, for example, programming implanted device 506 to acquire physiological data, programming implanted device 506 to perform at least one self-diagnostic test (such as for a device operational status), and programming implanted device 506 to deliver at least one therapy.

In one embodiment, programming implanted device 506 includes sending therapy parameters to implantable device 506. The therapy parameters provide an improved hemodynamic performance for a patient by delivering cardiac pacing pulses to the patient's heart. In one embodiment, the therapy parameters providing for the improved hemodynamic performance are determined by monitoring one or more ventricular diastolic hemodynamics as indicated by parameters related to heart sounds such as S3 and S4. Such parameters indicate the heart's mechanical activities and electromechanical association. In one specific embodiment, the acquisition of values of such parameters, the processing of the parameter values, and the subsequent determination of the therapy parameters are performed by system 100, as discussed above with reference to FIGS. 1-3.

FIG. 6 is a block diagram illustrating a specific embodiment of portions of cardiac rhythm management system 599. In this embodiment, system 100 is substantially included within implanted device 506. System 100 includes, as discussed above with reference to FIG. 1, acoustic sensor 110, sensor interface module 120, cardiac sensing circuit 112, heart sound detector 130, parameter generator 140, data acquisition timer 118, parameter processor 160, and therapy circuit 170. Implanted device 506 also includes, among other things, an implant telemetry module 672 and an implant antenna 674 to provide implanted device 506 with telemetry capability allowing it to communicate with external system 580 via telemetry link 570. In one embodiment, therapy circuit 170 includes a therapy controller that executes a predetermined therapy control algorithm to determine whether to deliver a therapy or adjust one or more therapy parameters based on the one or more of the heart sound-related parameter values generated by parameter generator 140 and trends and alert signal generated by parameter processor 160.

External system 580 includes, among other things, an external antenna 676, an external telemetry module 678, a controller 682, and a user interface 684. In one embodiment, external telemetry module 678 and external antenna 676 are included in external device 585 to provide external system 580 with capability of communicating with implanted device 506 through telemetry link 570 and external device 585. Controller 682 controls telemetry operation of external system 580, processes signals received from implanted device 506 for presentation on user interface 684, and processes user commands entered through user interface 684 for transmission to implanted device 506. In one embodiment, one or more of the heart-sound related parameter values, trends, and alert signal, as discussed above, are acquired by system 100 and telemetered to external system 580 via telemetry link 570. Controller 682 executes a predetermined therapy control algorithm to determine whether to deliver a therapy or adjust one or more therapy parameters based on the one or more of the heart sound-related parameter values, trends, and alert signal.

In one embodiment, system 100 is completely within a hermetically sealed can that houses at least portions of implanted device 506. Housing acoustic sensor 110 in the can has the advantage of minimizing the background noise associated with physical movements of the sensor, especially when acoustic sensor 110 includes an accelerometer. In another embodiment, acoustic sensor 110 is attached to a lead of lead system 508. This allows disposition of acoustic sensor 110 in or near heart 501 such that it is near the mechanical activities being the sources of the heart sounds of interest.

To include substantially the whole system 100 within implanted device 506 provides for the advantage of a self-contained implantable cardiac rhythm management system incorporating heart-sound based therapy control. In one embodiment, the heart-sound based therapy control using system 100 is able to function without telemetry link 570, for example, when the patient is outside the range of the telemetry communication. Implanted device 506 determines, without the intervention of the user or controller 682, whether to deliver a therapy or adjust one or more therapy parameters based on the one or more of the parameter values, trends, and alert signal generated within itself by system 100.

FIG. 7 is a block diagram illustrating another specific embodiment of portions of cardiac rhythm management system 599. In this embodiment, system 100 is partially included within implantable device 506 and partially included in external system 580. In one specific embodiment, parameter processor 160 is within external system 580, and the remaining components of system 100 are within implanted device 506. Parameter values generated by parameter generator 140 are telemetered to external system 580 via telemetry link 570 for further processing by parameter processor 160. In one embodiment, parameter processor 160 is included in external device 585. In an alternative embodiment, parameter processor 160 is included in remote device 595.

In one embodiment, the parameter values are telemetered as they are generated. In another embodiment, parameter values are first stored in memory circuit 146. Data acquisition enabler 118 times transmission of the parameter values in response to a command from external device 580 or on a predetermined schedule.

To include parameter processor 160 in external system 580 avoids placing the demand of energy and circuit resources required by parameter processor 160 in implanted device 506, which is subject to design restraints including power and size limitations. The advantages also include the feasibility of updating parameter processing algorithms used by parameter processor 160 without the need of replacing implanted device 506.

It is to be understood that the above detailed description is intended to be illustrative, and not restrictive. For example, system 100 may be incorporated into any implanted or external medical device providing for ECG and heart sound monitoring. Other embodiments will be apparent to those of skill in the art upon reading and understanding the above description. The scope of the invention should, therefore, be determined with reference to the appended claims, along with the full scope of equivalents to which such claims are entitled.

Claims

1. A system adapted to be coupled to a patient, the system comprising:

an acoustic sensor including an accelerometer adapted to sense an acoustic energy and produce an acoustic sensor signal indicative of heart sounds of the patient;
a cardiac sensing circuit adapted to sense a cardiac signal indicative of cardiac electrical events;
a heart sound detector coupled to the acoustic sensor and the cardiac sensing circuit, the heart sound detector adapted to detect selected heart sounds indicative of ventricular diastolic hemodynamic performance using the acoustic sensor signal and the cardiac signal;
a parameter generator coupled to the heart sound detector, the parameter generator adapted to generate values of at least one predetermined parameter related to the selected heart sounds; and
a processor coupled to the parameter generator, the processor adapted to perform a statistical process analyzing the values of the at least one predetermined parameter generated for a predetermined duration and produce at least one trend quantitatively presenting one or more ventricular diastolic filling pattern changes during the predetermined duration using an outcome of the statistical process.

2. The system of claim 1, comprising a data acquisition enabler adapted to time data acquisition by enabling one or more system components according to a predetermined schedule, the one or more system components including one or more of the acoustic sensor, the cardiac sensing circuit, the heart sound detector, and the parameter generator.

3. The system of claim 1, comprising a therapy circuit communicatively coupled to the processor, the therapy circuit adapted to deliver at least one cardiac therapy with at least one therapy parameter determined based on the at least one trend.

4. The system of claim 1, wherein the heart sound detector comprises a gating module coupled to the acoustic sensor and the cardiac sensing circuit, the gating module adapted to generate heart sound detection windows each timed for detection of one of the selected heart sounds based on a time of occurrence of one of selected cardiac electrical events.

5. The system of claim 4, wherein the accelerometer is adapted to produce an acoustic sensor signal indicative of the heart sounds of the patient and physical activities of the patient, and the parameter generator comprises:

a noise monitoring module adapted to produce a background noise level using the acoustic sensor signal, the background noise level indicative of physical activities of the patient; and
a screening module coupled to the noise monitoring module and adapted to exclude the values of the at least one predetermined parameter generated using the measurements made when the background noise level exceeds a predetermined level.

6. The system of claims 5, wherein the processor is adapted to compare the at least one trend to a threshold level and produce an output representative of an outcome of a trending analysis.

7. The system of claim 6, wherein the processor is adapted to generate the threshold level using the values of the at least one predetermined parameter measured during a second predetermined period of time.

8. The system of claim 5, wherein the parameter generator comprises a strength detector adapted to measure amplitudes each associated with a selected type of the selected heart sounds.

9. The system of claim 5, wherein the parameter generator comprises a relative strength detector adapted to determine differences each between amplitudes associated with two selected types of the selected heart sounds.

10. The system of claim 5, wherein the parameter generator comprises an electromechanical interval timer adapted to measure time intervals each between a selected type of the selected heart sounds and a selected type of the selected cardiac electrical events.

11. The system of claim 5, wherein the parameter generator comprises a mechanical interval timer adapted to measure time intervals each between two selected types of the selected type heart sounds.

12. The system of claim 5, wherein the parameter generator comprises a frequency analyzer adapted to compute a fundamental frequency associated with a selected type of the selected heart sounds.

13. A method, comprising:

sensing an acoustic energy to produce an acoustic sensor signal using an accelerometer, the acoustic signal indicative heart sounds of a patient;
sensing at least one cardiac signal indicative of cardiac electrical events;
detecting selected heart sounds indicative of ventricular diastolic hemodynamic performance using the acoustic sensor signal and the cardiac signal;
generating values of at least one predetermined parameter related to the selected heart sounds using the acoustic sensor signal and the cardiac signal;
performing a statistical process analyzing selected values of the at least one predetermined parameter, the selected values associated with the selected heart sounds detected during a first predetermined period of time; and
producing at least one trend quantitatively presenting one or more ventricular diastolic filling pattern changes during the predetermined period of time using an outcome of the statistical process.

14. The method of claim 13, comprising delivering at least one therapy with at least one parameter determined based on the at least one trend.

15. The method of claim 13, comprising:

comparing a quantity associated with the at least one trend to a threshold level; and
generating the threshold level using values of the at least one predetermined parameter measured during a second predetermined period of time.

16. The method of claim 15, comprising generating an alert signal indicative of a change in one of diastolic filling patterns using an outcome of comparing the quantity associated with the at least one trend to the threshold level.

17. The method of claim 13, comprising:

producing a background noise level using the acoustic sensor signal, the background noise level indicative of the physical activities of the patient;
excluding the values of the at least one predetermined parameter generated using the acoustic sensor signal measured when the background noise level exceeds a predetermined level.

18. The method of claim 17, wherein detecting selected heart sounds comprises detecting at least third heart sound (S3) and forth heart sounds (S4).

19. The method of claim 18, wherein generating values of at least one predetermined parameter comprises generating values of strength of S3 relative to S4.

20. The method of claim 18, wherein generating values of at least one predetermined parameter comprises generating values of time interval between S3 and an adjacently subsequent atrial contraction.

21. The method of claim 18, wherein detecting selected heart sounds further comprises detecting second heart sounds (S2), and generating values of at least one predetermined parameter comprises generating values of time interval between onsets of S3 and S2.

22. The method of claim 18, wherein generating values of at least one predetermined parameter comprises generating values of fundamental frequency of S3.

23. The method of claim 18, wherein generating values of at least one predetermined parameter comprises generating values of fundamental frequency of S4.

Referenced Cited
U.S. Patent Documents
3773033 November 1973 Rodbard et al.
3965339 June 22, 1976 Mount et al.
4094308 June 13, 1978 Cormier
4220160 September 2, 1980 Kimball et al.
4289141 September 15, 1981 Cormier
4428378 January 31, 1984 Anderson et al.
4428380 January 31, 1984 Wong et al.
4446872 May 8, 1984 Marsoner et al.
4548204 October 22, 1985 Groch et al.
4586514 May 6, 1986 Schlager et al.
4628939 December 16, 1986 Little et al.
4649930 March 17, 1987 Groch et al.
4674518 June 23, 1987 Salo
4686987 August 18, 1987 Salo et al.
4702253 October 27, 1987 Nappholz et al.
4712179 December 8, 1987 Heimer
4763646 August 16, 1988 Lekholm
4777960 October 18, 1988 Berger et al.
4796639 January 10, 1989 Snow et al.
4809697 March 7, 1989 Causey, III et al.
4825869 May 2, 1989 Sasmor et al.
4899751 February 13, 1990 Cohen
4905706 March 6, 1990 Duff et al.
4915113 April 10, 1990 Holman
4928688 May 29, 1990 Mower
4945909 August 7, 1990 Fearnot et al.
4967760 November 6, 1990 Bennett et al.
4981139 January 1, 1991 Pfohl
4989611 February 5, 1991 Zanetti et al.
5010889 April 30, 1991 Bredesen et al.
5012815 May 7, 1991 Bennett, Jr. et al.
5025809 June 25, 1991 Johnson et al.
5097831 March 24, 1992 Lekholm
5137019 August 11, 1992 Pederson et al.
5159932 November 3, 1992 Zanetti et al.
5179947 January 19, 1993 Meyerson et al.
5190035 March 2, 1993 Salo et al.
5218969 June 15, 1993 Bredesen et al.
5226413 July 13, 1993 Bennett et al.
5251626 October 12, 1993 Nickolls et al.
5282838 February 1, 1994 Hauser et al.
5284136 February 8, 1994 Hauck et al.
5292341 March 8, 1994 Snell
5301679 April 12, 1994 Taylor
5321618 June 14, 1994 Gessman
5334222 August 2, 1994 Salo et al.
5337752 August 16, 1994 Reeves
5365932 November 22, 1994 Greenhut
5372607 December 13, 1994 Stone et al.
5391190 February 21, 1995 Pederson et al.
5417717 May 23, 1995 Salo et al.
5421830 June 6, 1995 Epstein et al.
5472453 December 5, 1995 Alt
5487752 January 30, 1996 Salo et al.
5496361 March 5, 1996 Moberg et al.
5540727 July 30, 1996 Tockman et al.
5544661 August 13, 1996 Davis et al.
5549654 August 27, 1996 Powell
5554177 September 10, 1996 Kieval et al.
5584868 December 17, 1996 Salo et al.
5593431 January 14, 1997 Sheldon
5594638 January 14, 1997 Iliff
5607460 March 4, 1997 Kroll et al.
5630835 May 20, 1997 Brownlee
5674256 October 7, 1997 Carlson
5685317 November 11, 1997 Sjostrom
5687738 November 18, 1997 Shapiro et al.
5690690 November 25, 1997 Nappholz et al.
5697375 December 16, 1997 Hickey
5697959 December 16, 1997 Poore
5700283 December 23, 1997 Salo
5725562 March 10, 1998 Sheldon
5792195 August 11, 1998 Carlson et al.
5800473 September 1, 1998 Faisandier
5833623 November 10, 1998 Mann et al.
5836987 November 17, 1998 Baumann et al.
5860918 January 19, 1999 Schradi et al.
5860933 January 19, 1999 Don Michael
5891178 April 6, 1999 Mann et al.
5935081 August 10, 1999 Kadhiresan
5991657 November 23, 1999 Kim
5991661 November 23, 1999 Park et al.
6002777 December 14, 1999 Grasfield et al.
6015388 January 18, 2000 Sackner et al.
6016442 January 18, 2000 Hsu et al.
6022322 February 8, 2000 Prutchi
6026324 February 15, 2000 Carlson
6044297 March 28, 2000 Sheldon et al.
6044298 March 28, 2000 Salo et al.
6044299 March 28, 2000 Nilsson
6045513 April 4, 2000 Stone et al.
6053872 April 25, 2000 Mohler
6058329 May 2, 2000 Salo et al.
6064910 May 16, 2000 Andersson et al.
6077227 June 20, 2000 Miesel
6091990 July 18, 2000 Hsu et al.
6104949 August 15, 2000 Pitts et al.
6144880 November 7, 2000 Ding et al.
6152884 November 28, 2000 Bjorgaas
6161042 December 12, 2000 Hartley et al.
6168563 January 2, 2001 Brown
6190324 February 20, 2001 Kieval et al.
6193668 February 27, 2001 Chassaing et al.
6251126 June 26, 2001 Ottenhoff et al.
6264611 July 24, 2001 Ishikawa et al.
6269269 July 31, 2001 Ottenhoff et al.
6273856 August 14, 2001 Sun et al.
6275727 August 14, 2001 Hopper et al.
6278894 August 21, 2001 Salo et al.
6280409 August 28, 2001 Stone et al.
6298269 October 2, 2001 Sweeney
6312378 November 6, 2001 Bardy
6351672 February 26, 2002 Park et al.
6351673 February 26, 2002 Ding et al.
6360127 March 19, 2002 Ding et al.
6361522 March 26, 2002 Scheiner et al.
6366811 April 2, 2002 Carlson
6368283 April 9, 2002 Xu et al.
6370424 April 9, 2002 Prutchi
6383136 May 7, 2002 Jordan
6409675 June 25, 2002 Turcott
6411840 June 25, 2002 Bardy
6415033 July 2, 2002 Halleck et al.
6438407 August 20, 2002 Ousdigian et al.
6440082 August 27, 2002 Joo et al.
6459929 October 1, 2002 Hopper et al.
6466821 October 15, 2002 Pianca et al.
6477406 November 5, 2002 Turcott
6478746 November 12, 2002 Chassaing et al.
6480733 November 12, 2002 Turcott
6491639 December 10, 2002 Turcott
6520924 February 18, 2003 Lee
6527729 March 4, 2003 Turcott
6542775 April 1, 2003 Ding et al.
6575916 June 10, 2003 Halleck et al.
6584353 June 24, 2003 Meyer
6625493 September 23, 2003 Kroll et al.
6626842 September 30, 2003 Oka
6643548 November 4, 2003 Mai et al.
6650940 November 18, 2003 Zhu et al.
6658292 December 2, 2003 Kroll et al.
6665564 December 16, 2003 Lincoln et al.
6666826 December 23, 2003 Salo et al.
6684103 January 27, 2004 Ding et al.
6719701 April 13, 2004 Lade
6733464 May 11, 2004 Olbrich et al.
6752765 June 22, 2004 Jensen et al.
6792308 September 14, 2004 Corbucci
6795732 September 21, 2004 Stadler et al.
6810284 October 26, 2004 Bradley
6810287 October 26, 2004 Zhu et al.
6824519 November 30, 2004 Narimatsu et al.
6827690 December 7, 2004 Bardy
6830548 December 14, 2004 Bonnet et al.
6845263 January 18, 2005 Kawaguchi
6885889 April 26, 2005 Chinchoy
6913577 July 5, 2005 Bardy
6942622 September 13, 2005 Turcott
6961617 November 1, 2005 Snell
6963777 November 8, 2005 Lincoln et al.
6980851 December 27, 2005 Zhu et al.
7010342 March 7, 2006 Galen et al.
7043305 May 9, 2006 Kenknight et al.
7065397 June 20, 2006 Galen et al.
7072708 July 4, 2006 Andersen et al.
7074195 July 11, 2006 Nelson et al.
7079895 July 18, 2006 Verbeek et al.
7079896 July 18, 2006 Park et al.
7110804 September 19, 2006 Baumer et al.
7110817 September 19, 2006 Yu et al.
7113825 September 26, 2006 Pastore et al.
7115096 October 3, 2006 Siejko et al.
7123962 October 17, 2006 Siejko et al.
7127290 October 24, 2006 Girouard et al.
7139609 November 21, 2006 Min et al.
7158830 January 2, 2007 Yu et al.
7177685 February 13, 2007 Lincoln et al.
7206636 April 17, 2007 Turcott
7248923 July 24, 2007 Maile et al.
7366568 April 29, 2008 Pastore et al.
7387610 June 17, 2008 Stahmann et al.
7400928 July 15, 2008 Hatlestad
7404802 July 29, 2008 Siejko et al.
7424321 September 9, 2008 Wariar et al.
7431699 October 7, 2008 Siejko et al.
7480528 January 20, 2009 Brockway et al.
7493162 February 17, 2009 Girouard et al.
7559901 July 14, 2009 Maile et al.
7582061 September 1, 2009 Li et al.
7585279 September 8, 2009 Carlson et al.
7662101 February 16, 2010 Lee et al.
7662104 February 16, 2010 Siejko et al.
7668594 February 23, 2010 Brockway et al.
7713213 May 11, 2010 Siejko et al.
7736319 June 15, 2010 Patangay et al.
7751890 July 6, 2010 McCabe et al.
7780606 August 24, 2010 Carlson et al.
7844334 November 30, 2010 Maile et al.
7922669 April 12, 2011 Zhang et al.
7972275 July 5, 2011 Siejko et al.
8000780 August 16, 2011 Wariar et al.
8048001 November 1, 2011 Patangay et al.
20010007053 July 5, 2001 Bardy
20020001390 January 3, 2002 Kawaguchi
20020019586 February 14, 2002 Teller et al.
20020026103 February 28, 2002 Norris et al.
20020026223 February 28, 2002 Riff et al.
20020035337 March 21, 2002 Oka
20020072684 June 13, 2002 Stearns
20020082645 June 27, 2002 Sweeney
20020107450 August 8, 2002 Ogura
20020120298 August 29, 2002 Kramer et al.
20020128563 September 12, 2002 Carlson et al.
20020147401 October 10, 2002 Oka
20020151812 October 17, 2002 Scheiner et al.
20020151938 October 17, 2002 Corbucci
20030055352 March 20, 2003 Hayek et al.
20030055461 March 20, 2003 Girouard et al.
20030069608 April 10, 2003 Sweeney
20030072458 April 17, 2003 Halleck et al.
20030078624 April 24, 2003 Carlson et al.
20030093002 May 15, 2003 Kuo
20030093003 May 15, 2003 Watrous et al.
20030105496 June 5, 2003 Yu et al.
20030120159 June 26, 2003 Mohler
20030125774 July 3, 2003 Salo
20030144702 July 31, 2003 Yu et al.
20030144703 July 31, 2003 Yu et al.
20030158492 August 21, 2003 Sheldon et al.
20030158584 August 21, 2003 Cates et al.
20030171791 September 11, 2003 KenKnight et al.
20030176896 September 18, 2003 Lincoln et al.
20030191503 October 9, 2003 Zhu et al.
20030208240 November 6, 2003 Pastore et al.
20030216620 November 20, 2003 Jain et al.
20030229289 December 11, 2003 Mohler
20040024423 February 5, 2004 Lincoln et al.
20040039295 February 26, 2004 Olbrich et al.
20040039419 February 26, 2004 Stickney et al.
20040039420 February 26, 2004 Jayne et al.
20040064056 April 1, 2004 Ogura
20040078059 April 22, 2004 Ding et al.
20040078060 April 22, 2004 Ding et al.
20040102712 May 27, 2004 Belalcazar et al.
20040106960 June 3, 2004 Siejko et al.
20040106961 June 3, 2004 Siejko et al.
20040106962 June 3, 2004 Mai et al.
20040111040 June 10, 2004 Ni et al.
20040122484 June 24, 2004 Hatlestad et al.
20040127792 July 1, 2004 Siejko et al.
20040138572 July 15, 2004 Thiagarajan
20040167417 August 26, 2004 Schulhauser et al.
20040215264 October 28, 2004 Van Bentem
20040225332 November 11, 2004 Gebhardt et al.
20040236239 November 25, 2004 Murray et al.
20040243192 December 2, 2004 Hepp et al.
20040254481 December 16, 2004 Brodnick
20040267147 December 30, 2004 Sullivan
20040267148 December 30, 2004 Arand et al.
20050004485 January 6, 2005 Crosby et al.
20050027323 February 3, 2005 Mulligan et al.
20050033190 February 10, 2005 Bauer
20050060001 March 17, 2005 Singhal et al.
20050065448 March 24, 2005 Stahmann et al.
20050065556 March 24, 2005 Reghabi et al.
20050090870 April 28, 2005 Hine et al.
20050102001 May 12, 2005 Maile et al.
20050102002 May 12, 2005 Salo et al.
20050148896 July 7, 2005 Siejko et al.
20050148897 July 7, 2005 Cho et al.
20050149136 July 7, 2005 Siejko et al.
20050203579 September 15, 2005 Sowelam et al.
20050222515 October 6, 2005 Polyshchuk et al.
20050256542 November 17, 2005 Pastore et al.
20060020294 January 26, 2006 Brockway et al.
20060020295 January 26, 2006 Brockway et al.
20060025699 February 2, 2006 Maile et al.
20060030892 February 9, 2006 Kadhiresan et al.
20060161070 July 20, 2006 Siejko et al.
20060259087 November 16, 2006 Baynham et al.
20060259088 November 16, 2006 Pastore et al.
20060270939 November 30, 2006 Wariar et al.
20060282000 December 14, 2006 Zhang et al.
20070078491 April 5, 2007 Siejko et al.
20070150005 June 28, 2007 Sih et al.
20070239218 October 11, 2007 Carlson et al.
20080071315 March 20, 2008 Baynham et al.
20080103406 May 1, 2008 Kameli
20080119749 May 22, 2008 Haro et al.
20100099997 April 22, 2010 Siejko et al.
20100249863 September 30, 2010 Carlson et al.
20120271186 October 25, 2012 Siejko et al.
Foreign Patent Documents
0297675 January 1989 EP
0709058 May 1996 EP
1179317 February 2002 EP
1247485 October 2002 EP
61202653 September 1986 JP
63-109103 July 1988 JP
63-290544 November 1988 JP
03015441 January 1991 JP
04-082538 March 1992 JP
06-277189 October 1994 JP
2000-060846 February 2000 JP
2000316825 November 2000 JP
2001145606 May 2001 JP
2004-081854 March 2004 JP
4576236 November 2010 JP
WO-0041765 July 2000 WO
WO-0041766 July 2000 WO
WO-0103575 January 2001 WO
WO-0122885 April 2001 WO
WO-0124876 April 2001 WO
WO-0156651 August 2001 WO
WO-0167948 September 2001 WO
WO-2004012815 February 2004 WO
WO-2004050178 June 2004 WO
WO-2004060483 July 2004 WO
WO-2004/066825 August 2004 WO
WO-2005/074361 August 2005 WO
WO-2005122902 December 2005 WO
WO-2006028575 March 2006 WO
WO-2006078757 July 2006 WO
WO-2006127594 November 2006 WO
Other references
  • U.S. Appl. No. 10/334,694, Advisory Action mailed Dec. 18, 2007, 3 pgs.
  • U.S. Appl. No. 10/334,694, Advisory Action mailed Dec. 23, 2008, 3 pgs.
  • U.S. Appl. No. 10/334,694, Final Office Action mailed Oct. 1, 2007, 13 pgs.
  • U.S. Appl. No. 10/334,694, Final Office Action mailed Oct. 7, 2008, 14 pgs.
  • U.S. Appl. No. 10/334,694, Final Office Action mailed Nov. 27, 2009, 13 pgs.
  • U.S. Appl. No. 10/334,694, Non-Final Office Action mailed Mar. 18, 2009, 14 pgs.
  • U.S. Appl. No. 10/334,694, Non-Final Office Action mailed Mar. 19, 2008, 15 pgs.
  • U.S. Appl. No. 10/334,694, Non-Final Office Action mailed Apr. 20, 2007, 12 pgs.
  • U.S. Appl. No. 10/334,694, Non-Final Office Action mailed Apr. 30, 2010, 13 pgs.
  • U.S. Appl. No. 10/334,694, Non-Final Office Action mailed Nov. 27, 2006, 9 pgs.
  • U.S. Appl. No. 10/334,694, Notice of Allowance mailed Mar. 4, 2011, 7 pgs.
  • U.S. Appl. No. 10/334,694, Notice of Allowance mailed Oct. 5, 2010, 6 pgs.
  • U.S. Appl. No. 10/334,694, Response filed Feb. 27, 2007 to Non-Final Office Action mailed Nov. 27, 2007, 20 pgs.
  • U.S. Appl. No. 10/334,694, Response filed Mar. 1, 2010 to Final Office Action mailed Nov. 27, 2009, 21 pgs.
  • U.S. Appl. No. 10/334,694, Response filed Jun. 19, 2008 to Non-Final Office Action mailed Mar. 19, 2008, 20 pgs.
  • U.S. Appl. No. 10/334,694, Response filed Jul. 17, 2009 to Non Final Office Action mailed Mar. 18, 2009, 18 pgs.
  • U.S. Appl. No. 10/334,694, Response filed Jul. 20, 2007 to Non-Final Office Action mailed Apr. 20, 2007, 18 pgs.
  • U.S. Appl. No. 10/334,694, Response filed Jul. 27, 2010 to Non Final Office Action mailed Apr. 30, 2010, 19 pgs.
  • U.S. Appl. No. 10/334,694, Response filed Dec. 3, 2007 to Final Office Action mailed Oct. 1, 2007, 21 pgs.
  • U.S. Appl. No. 10/334,694, Response filed Dec. 8, 2008 to Final Office Action mailed Oct. 7, 2008, 18 pgs.
  • European Serial Application No. 10158651.9, Extended European Search Report mailed on Jul. 29, 2010, 6 pgs.
  • European Application Serial No. 03800278.8, Communication dated Oct. 17, 2007, 4 pgs.
  • European Application Serial No. 03800278.8, Response filed Feb. 18, 2008 to Communication dated Oct. 17, 2007, 14 pgs.
  • European Divisional Application Serial No. 10158651.9, Response filed Feb. 28, 2011 to EP Search Report mailed Jul. 29, 2010, 2.
  • International Application Serial No. PCT/US03/41481, International Search Report mailed Jun. 4, 2004, 7 pgs.
  • Japanese Application Serial No. 2004-565783, Amendment and Argument filed Feb. 5, 2010 to Office Action Mailed Nov. 11, 2009, (w/ English Translation of Amended Claims), 14 pgs.
  • Japanese Application Serial No. 2004-565783, Notice of Allowance mailed Aug. 9, 2010, 2 pgs.
  • Japanese Application Serial No. 2004-565783, Office Action mailed Mar. 11, 2010, (w/ English Translation), 4 pgs.
  • Japanese Application Serial No. 2004-565783, Office Action mailed Nov. 11, 2009, (w/ English Translation), 4 pgs.
  • Aaron, S. D, et al., “How accurate is spirometry at predicting restrictive pulmonary impairment?”, Chest, 115(3), XP002362629 ISSN: 0012-3692, (Mar. 1999), 869-873.
  • Amende, I., “Hemodynamics in ischemia: diastolic phase”, Z. Kardiol., 73 Suppl 2, [Article in German With English Abstract], (1984), 127-33.
  • Barbaro, V., et al., “A portable unit for remote monitoring of pacemaker patients”, Journal of Telemedicine and Telecare, 3(2), (1997), 96-102.
  • Bulgrin, J. R, et al., “Comparison of Short-Time Fourier, Wavelet and Time-Domain Analyses of Intracardiac Sounds”, Biomedical Sciences Instrumentation, 29, (1993), 4 pgs.
  • Collins, Sean, “Diagnostic Utility of an S3 in Dyspneic ED Patients”, Inovise Medical Inc, University of Cincinnati Medical Center, (2005), 6 pgs.
  • Hutten, H., et al., “Cardiac Telemonitoring through the Linkage of Close-up Telemetry and Internet Transmission”, Institute for Electro-and Biomedical Technology, Technical University of Graz Inffeldgasse, 42, [Article in German with English Abstract], (1997), 67-69.
  • Leatham, A, “Splitting of the First and Second Heart Sounds”, Lancet, 267 (6839), (Sep. 25, 1954), 607-614.
  • Marcus, G. M., et al., “Association Between Phonocardiographic Third and Fourth Heart Sounds and Objective Measures of Left Ventricular Function”, JAMA, 293(18), (May 11, 2005), 2238-44.
  • Obaidat, M. S, et al., “Performance of the Short-Time Fourier Transform and Wavelet Transform to Phonocardiogram Signal Analysis”, Proceedings of the 1992 ACM/SIGAPP Symposium on Applied Computing ACM, Applied Computing: Technological Challenges of the 1990s, (1992), 856-862.
  • Smith, Damon, et al., “Influence of the Aortic Component of the Second Heart Sound on Left Ventricular Maximal Negative dP/dt in the Dog”, Am. J. Cardiol., 55: 205, (1985), 205-209.
  • Wood, J. C, et al., “Time-Frequency Transforms: A New Approach to First Heart Sound Frequency Dynamics”, IEEE Transactions on Biomedical Engineering, 39 (7), IEEE Service Center, US, (Jul. 1, 1992), 730-740.
  • European Application Serial No. 10158651.9, Examination Notification Art. 94(3) mailed Jul. 20, 2011, 5 pgs.
  • European Application Serial No. 10158651.9, Response filed Nov. 29, 2011 to Office Action mailed Jul. 20, 2011, 10 pgs.
  • Japanese Application Serial No. 2004-565783, Amendment and Response filed Jun. 2, 2010 to Office Action mailed Mar. 11, 2010, (w/ English Translation of Amended Claims), 14 pgs.
Patent History
Patent number: 8636669
Type: Grant
Filed: Jan 5, 2011
Date of Patent: Jan 28, 2014
Patent Publication Number: 20110098588
Assignee: Cardiac Pacemakers, Inc. (St. Paul, MN)
Inventors: Krzysztof Z. Siejko (Maple Grove, MN), Qingsheng Zhu (Wexford, PA), Gerrard M. Carlson (Champlin, MN)
Primary Examiner: Joseph Stoklosa
Application Number: 12/985,055
Classifications
Current U.S. Class: Detecting Heart Sound (600/528); Detecting Heartbeat Electric Signal And Diverse Cardiovascular Characteristic (600/513)
International Classification: A61B 5/02 (20060101);